Various climate models have been developed to analyze and predict climate change; however, model uncertainties cannot be easily overcome. A statistical approach has been presented in this paper to calculate the distributions of future climate change based on an ensemble of the Weather Research and Forecasting (WRF) models. Wavelet analysis has been adopted to de-noise the WRF model output. Using the de-noised model output, we carry out Bayesian analysis to decrease uncertainties in model CAM_KF, RRTM_KF and RRTM_GRELL for each downscaling region. / text

Numerical modeling of shallow microtidal semi-enclosed estuaries requires the effective simulation of physical processes with a wide range of temporal and spatial scales. In theory, application of sufficient grid resolution in both the horizontal and vertical should result in a reasonable simulation. However, in practice, this is not the case. Fully resolving the finest scales can be computationally prohibitive, and various algorithmic assumptions can break down at fine resolutions, leading to spurious oscillations in the solution. One method of simulating inherently cross-scale phenomena is to use multimodel approaches in which domain decomposition is used to divide the region into multiple subregions, each modeled by different submodels. These submodels are coupled to simulate the entire system efficiently. In general, the different models may involve different physics, they may be dimensionally heterogeneous or they may be both physically and dimensionally heterogeneous. A reduction in computational expense is obtained by using simpler physics and/or a reduced dimension model in the submodels. In this research, we look at the particular case of modeling shallow bays containing narrow, deep ship channels. In order to accurately model bay circulation, a model should capture the effect of these spatially localized navigational channels. Our research shows that modeling techniques currently used to simulate such systems using 2 dimensional or coarse resolution 3 dimensional estuary models misrepresent wind driven surface circulation in the shallow bay and tide driven volume fluxes through the channel. Fully resolving the geometry of the ship channel is impractical on all but large parallel computing clusters. We propose a more efficient method using the multimodel approach. This approach splits the estuary into a shallow bay region and a subsurface ship channel region. By separating the physical domain into two parts in this way, simpler models can be used that are targeted at the different physical processes and geometries dominant in each region. By using a low resolution 3D model (SELFE) in the shallow bay region, coupled through appropriate interface conditions with a 2D laterally averaged model, the effects of the ship channel on bay circulation are accurately represented at a fraction of the computational expense. In this research, this coupled model was developed and applied to an ideal shallow bay- ship channel system. The coupled model approach is found to be an effective strategy for modeling this type of system. / text

Climate change is one of the most challenging and defining issues that has resulted in substantial societal, economic, and environmental impacts across the world. To assess the potential climate change impact, climate projections are generated with General Circulation Models (GCMs). However, the climate change signals remain uncertain and GCMs have difficulty in representing regional climate features. Therefore, comprehensive knowledge of climate change signals and reliable high-resolution climate projections are highly desired. This dissertation aims to address such challenges by developing climate projections with multi-model ensembles for climate impact assessment. This includes: i) developing multi-model ensembles to analyze global changes in all water components within the hydrological cycle and quantify the uncertainties with GCM projections; ii) development of bias correction models for generating high-resolution daily maximum and minimum temperature projections with individual GCMs and multi-model ensemble means over Canada; iii) proposing bias correction models with individual GCMs and multi-model ensemble means for high-resolution daily precipitation projections for Canada. The proposed models are capable of developing high-resolution climate projections at a regional scale and exploring the climate change signals. The reliable climate projections generated could provide valuable information for formulating appropriate climate change mitigation and adaptation strategies across the world. / Thesis / Doctor of Philosophy (PhD)

An important objective in statistical risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs) that induce a pre-specified Benchmark Response (BMR) in a target population. Established inferential approaches for BMD analysis typically involve one-sided, frequentist confidence limits, leading in practice to what are called Benchmark Dose Lower Limits (BMDLs). Appeal to hierarchical Bayesian modeling and credible limits for building BMDLs is far less developed, however. Indeed, for the few existing forms of Bayesian BMDs, informative prior information is seldom incorporated. Here, a new method is developed by using reparameterized quantal-response models that explicitly describe the BMD as a target parameter. This potentially improves the BMD/BMDL estimation by combining elicited prior belief with the observed data in the Bayesian hierarchy. Besides this, the large variety of candidate quantal-response models available for applying these methods, however, lead to questions of model adequacy and uncertainty. Facing this issue, the Bayesian estimation technique here is further enhanced by applying Bayesian model averaging to produce point estimates and (lower) credible bounds. Implementation is facilitated via a Monte Carlo-based adaptive Metropolis (AM) algorithm to approximate the posterior distribution. Performance of the method is evaluated via a simulation study. An example from carcinogenicity testing illustrates the calculations.

La forte et rapide croissance de l’énergie éolienne à travers le monde a nécessité la mise en vigueur de nouveaux critères normalisés permettant de l’intégrer dans les réseaux électriques sans affecter la qualité et la stabilité du système, et qui peuvent demander aux éoliennes de participer au réglage de la fréquence dans les réseaux en cas de besoin. Ainsi, les travaux présentés dans cette thèse visent à proposer une solution de loi de commande qui permette aux éoliennes de participer au réglage de la fréquence du réseau. En analysant les limites des correcteurs classiques de types P, PI et PID, nous avons opté pour la commande LQ munie d’une approche multimodèle et qui a montré de bonnes performances aux résultats de simulation. Certaines améliorations ont été ajoutées à cette loi de commande du genre modèle de référence, action intégrale, … afin de permettre une poursuite de puissance autour d’une référence donnée qui change selon la fréquence du réseau / The fast and big growth of wind power around the world required the implementation of new standardized criteria to integrate this kind of energy into electric networks without affecting the quality and stability of the system. These criteria could ask the wind turbines to participate in the network frequency control when necessary. Thus, the works presented in this thesis aim to provide a control law solution that allows wind turbines to participate the grid frequency control. By analyzing the limits of traditional regulators such as P, PI and PID, we opted for the LQ controller combined to a multi-model approach because of the good performances shown in the simulation results. Some improvements were added to this control law: reference model, integral action, ... to allow a power trucking for a given reference that changes with the grid frequency

O sistema de produção da cana-de-açúcar é altamente complexo e a expansão do cultivo tem ocorrido para locais com considerável déficit hídrico (DH). Nesse contexto, o DH e o manejo agrícola são os principais fatores determinantes das quebras de produtividade da cana-de-açúcar, sendo a irrigação uma das alternativas para minimizá-las. Modelos de simulação podem ser utilizados para avaliar a quebra de produtividade e os impactos da irrigação na cana-de-açúcar. Assim, o presente estudo teve por objetivos: i) avaliar e ajustar os modelos MZA-FAO, DSSAT/CANEGRO e APSIM-Sugarcane e propor um fator de manejo (kdec); ii) avaliar a magnitude da quebra de produtividade e suas causas (DH e manejo); iii) avaliar os impactos da irrigação na produtividade da cana-de-açúcar e; iv) estimar o número de dias de suspensão da irrigação antes da colheita. Comparando-se com dados de produtividade de cana de 12 meses com diversos cortes e sistemas (sequeiro e irrigado) para diversas regiões brasileiras, o desempenho de todos os modelos foi fraco com grande erro absoluto médio (EAM > 29 t ha-1) e baixa precisão (R2 < 0,54), já que esses não consideram o manejo agrícola. A introdução do kdec propiciou melhoria no desempenho dos modelos (EAM < 14 t ha-1 e R2 &ge; 0,63). Utilizando a média de produtividade dos três modelos, a precisão e acurácia melhoraram e o EAM diminuiu. Para o estudo da quebra de produtividade foram utilizadas simulações apenas de cana planta de 12 meses sob manejo ótimo, por meio da abordagem multimodelos, as quais foram contrastadas com os dados do IBGE para 30 locais. A quebra de produtividade total média (QT) foi 121 t ha-1, sendo que a maior parte desta foi devido ao DH (72% da QT ou 87 t ha-1). A quebra de produtividade devido ao manejo agrícola (QM) depende da região e das práticas adotados pelos produtores sendo, em média, 28% da QT (34 t ha-1). A QM pode estar relacionada, principalmente, ao monocultivo e à mecanização. Uma vez que o DH é a principal causa da quebra de produtividade, o impacto da irrigação nesta foi estimado por meio de simulações para cana planta de 12 meses em três tipos de solo e 12 datas de plantio com o modelo MZA-FAO. Os resultados demonstraram que o incremento na produtividade decorrente do uso da irrigação é dependente da interação entre as condições meteorológicas, do solo, da época de plantio e da lâmina de irrigação, e revelam que tal prática tem potencial para melhorar os níveis de produtividade em diversas regiões brasileiras. A suspensão da irrigação antes da colheita é uma estratégia para incrementar o teor e a produtividade de sacarose, todavia, não há recomendações para as condições brasileiras. Na tentativa de fornecer informações para nortear tal estratégia, simulações com o modelo APSIM-Sugarcane para cana planta de 12 meses foram realizadas para diferentes tipos de solo, épocas de colheita e locais. O número de dias de suspensão da irrigação variou entre 15 e 115 dias, dependendo da localidade, do solo e da época da colheita. / The sugarcane production system is highly complex and the expansion of this crop is occurring to areas with expressive water deficit (WD). In this context, WD and crop management (CM) are the main determining factors of yield gaps (YG). Irrigation is an alternative to reduce YG of this crop. Crop simulation models can be used to evaluate the YG and irrigation impacts on sugarcane production. Based on that, this study aimed: i) to evaluate and adjust the MZA-FAO, DSSAT/CANEGRO and APSIM-Sugarcane models and propose a management factor (kdec) to improve the performance of these models; ii) to assess the YG magnitude and its causes (WD and CM); iii) to evaluate the impacts of irrigation on sugarcane yield and; iv) to estimate the drying-off days before harvest for different locations. When comparing 12-month cane data with several cuts in rainfed and irrigated systems, the performance of all models was poor with high mean absolute error (MAE > 29 t ha-1) and low precision (R2 < 0.54), once the models does not take into account crop management aspects. The introduction of kdec increased the models\' performances, with MAE < 14 ta ha-1 and R2 &ge; 0.63. When the average yield of the three models was used, the precision and accuracy improved and MAE decreased. The YG was calculated by the difference between simulated values of 12-months plant cane under optimum management in a multi-model approach and data from IBGE for 30 locations. The average YG total (YGT) was 121 t ha-1, which were mainly caused by WD (YGWD), followed by sub-optimal CM (YGCM). The YGWD accounted for about 72% of YGT (&sim; 87 t ha-1). The YGCM is dependent on the region and practices adopted by growers, and it represents, in average, 28% of the YGT (34 t ha-1). YGCM can be related mainly to monoculture and mechanization of high impact. Since the WD is the main cause of YG, the impact of irrigation on sugarcane yield was estimated by simulating 12-month plant cane in three soil types and 12 planting dates with MZA-FAO model for a long-term period (30 years). The results showed that the yield increases depend on the interaction between weather conditions, soil type, planting date and irrigation level. The simulations showed that irrigation is a practice with great potential to increase the sugarcane yield in several Brazilian locations. When sugarcane is irrigated, the drying-off is a strategy to increase sucrose content and yield; however, there are no recommendations about it for Brazilian conditions. In order to address this issue, simulations were conducted with APSIM-Sugarcane model for 12-month plant cane under optimum management in three soil types and 12 Brazilian locations for a long-term period (30 years). The harvest dates were simulated from May to November, which is the common harvesting season in sugarcane mills in the evaluated regions. The number of drying-off days varies according to location, soil type and harvest date, with the median ranging from 15 to 115 days.

O sistema de produção da cana-de-açúcar é altamente complexo e a expansão do cultivo tem ocorrido para locais com considerável déficit hídrico (DH). Nesse contexto, o DH e o manejo agrícola são os principais fatores determinantes das quebras de produtividade da cana-de-açúcar, sendo a irrigação uma das alternativas para minimizá-las. Modelos de simulação podem ser utilizados para avaliar a quebra de produtividade e os impactos da irrigação na cana-de-açúcar. Assim, o presente estudo teve por objetivos: i) avaliar e ajustar os modelos MZA-FAO, DSSAT/CANEGRO e APSIM-Sugarcane e propor um fator de manejo (kdec); ii) avaliar a magnitude da quebra de produtividade e suas causas (DH e manejo); iii) avaliar os impactos da irrigação na produtividade da cana-de-açúcar e; iv) estimar o número de dias de suspensão da irrigação antes da colheita. Comparando-se com dados de produtividade de cana de 12 meses com diversos cortes e sistemas (sequeiro e irrigado) para diversas regiões brasileiras, o desempenho de todos os modelos foi fraco com grande erro absoluto médio (EAM > 29 t ha-1) e baixa precisão (R2 < 0,54), já que esses não consideram o manejo agrícola. A introdução do kdec propiciou melhoria no desempenho dos modelos (EAM < 14 t ha-1 e R2 &ge; 0,63). Utilizando a média de produtividade dos três modelos, a precisão e acurácia melhoraram e o EAM diminuiu. Para o estudo da quebra de produtividade foram utilizadas simulações apenas de cana planta de 12 meses sob manejo ótimo, por meio da abordagem multimodelos, as quais foram contrastadas com os dados do IBGE para 30 locais. A quebra de produtividade total média (QT) foi 121 t ha-1, sendo que a maior parte desta foi devido ao DH (72% da QT ou 87 t ha-1). A quebra de produtividade devido ao manejo agrícola (QM) depende da região e das práticas adotados pelos produtores sendo, em média, 28% da QT (34 t ha-1). A QM pode estar relacionada, principalmente, ao monocultivo e à mecanização. Uma vez que o DH é a principal causa da quebra de produtividade, o impacto da irrigação nesta foi estimado por meio de simulações para cana planta de 12 meses em três tipos de solo e 12 datas de plantio com o modelo MZA-FAO. Os resultados demonstraram que o incremento na produtividade decorrente do uso da irrigação é dependente da interação entre as condições meteorológicas, do solo, da época de plantio e da lâmina de irrigação, e revelam que tal prática tem potencial para melhorar os níveis de produtividade em diversas regiões brasileiras. A suspensão da irrigação antes da colheita é uma estratégia para incrementar o teor e a produtividade de sacarose, todavia, não há recomendações para as condições brasileiras. Na tentativa de fornecer informações para nortear tal estratégia, simulações com o modelo APSIM-Sugarcane para cana planta de 12 meses foram realizadas para diferentes tipos de solo, épocas de colheita e locais. O número de dias de suspensão da irrigação variou entre 15 e 115 dias, dependendo da localidade, do solo e da época da colheita. / The sugarcane production system is highly complex and the expansion of this crop is occurring to areas with expressive water deficit (WD). In this context, WD and crop management (CM) are the main determining factors of yield gaps (YG). Irrigation is an alternative to reduce YG of this crop. Crop simulation models can be used to evaluate the YG and irrigation impacts on sugarcane production. Based on that, this study aimed: i) to evaluate and adjust the MZA-FAO, DSSAT/CANEGRO and APSIM-Sugarcane models and propose a management factor (kdec) to improve the performance of these models; ii) to assess the YG magnitude and its causes (WD and CM); iii) to evaluate the impacts of irrigation on sugarcane yield and; iv) to estimate the drying-off days before harvest for different locations. When comparing 12-month cane data with several cuts in rainfed and irrigated systems, the performance of all models was poor with high mean absolute error (MAE > 29 t ha-1) and low precision (R2 < 0.54), once the models does not take into account crop management aspects. The introduction of kdec increased the models\' performances, with MAE < 14 ta ha-1 and R2 &ge; 0.63. When the average yield of the three models was used, the precision and accuracy improved and MAE decreased. The YG was calculated by the difference between simulated values of 12-months plant cane under optimum management in a multi-model approach and data from IBGE for 30 locations. The average YG total (YGT) was 121 t ha-1, which were mainly caused by WD (YGWD), followed by sub-optimal CM (YGCM). The YGWD accounted for about 72% of YGT (&sim; 87 t ha-1). The YGCM is dependent on the region and practices adopted by growers, and it represents, in average, 28% of the YGT (34 t ha-1). YGCM can be related mainly to monoculture and mechanization of high impact. Since the WD is the main cause of YG, the impact of irrigation on sugarcane yield was estimated by simulating 12-month plant cane in three soil types and 12 planting dates with MZA-FAO model for a long-term period (30 years). The results showed that the yield increases depend on the interaction between weather conditions, soil type, planting date and irrigation level. The simulations showed that irrigation is a practice with great potential to increase the sugarcane yield in several Brazilian locations. When sugarcane is irrigated, the drying-off is a strategy to increase sucrose content and yield; however, there are no recommendations about it for Brazilian conditions. In order to address this issue, simulations were conducted with APSIM-Sugarcane model for 12-month plant cane under optimum management in three soil types and 12 Brazilian locations for a long-term period (30 years). The harvest dates were simulated from May to November, which is the common harvesting season in sugarcane mills in the evaluated regions. The number of drying-off days varies according to location, soil type and harvest date, with the median ranging from 15 to 115 days.

As robustness of social science is getting more attention, analytical choices have been found to be more important than previously thought. This thesis investigates robustness of intergenerational educational mobility estimates using multiverse analysis, a technique for incorporating many analyses into one framework while varying analytical choices such as variable coding, mobility measures, and exclusion criteria. Using ESS data from 16 European countries over nine survey rounds, results show substantial variation in point estimates, which in turn creates high variation in rankings of European countries. The conclusion is that analytical choices play an important role in calculating educational mobility estimates, and that ranking of European countries according to intergenerational mobility estimates is sensitive to varying these choices. Future mobility research should take this into account.

Die Planung und Ausführung von Bauwerken basiert auf Informationsprozesse, in denen verknüpfte Fachmodelle verschiedener Baudomänen als fachübergreifende Informationsräume verwendet werden. Dabei führen erhöhte Anforderungen an spezialisierte Arbeitsschritte sowie die wachsende Komplexität der Bauprojekte zu einem Anwachsen der Menge, des Umfangs und der Komplexität der ausgetauschten Informationsräume. Bei der Betrachtung des Informationsbedarfs der Bauinformationsprozesse lässt sich eine Kontextabhängigkeit erkennen, in der verschiedene Aspekte des Bearbeitungskontextes sowohl die Menge und Qualität als auch die Ausschnitte und Verknüpfungstiefe der erforderlichen Informationsräume determinieren. Die vorliegende Arbeit befasst sich mit der kontextgerechten Informationsversorgung von Informationsprozessen im Bauwesen. Auf der Grundlage multimodellbasierter Informationsräume wird ein Ansatz vorgestellt, der die Kontextabhängigkeit des Informationsbedarfs durch kontextadaptive Multimodellvorlagen formalisiert und entsprechende kontextgerechte Informationsräume erzeugt. Dafür werden in einem ersten Schritt der Bearbeitungskontext von Bauinformationsprozessen betrachtet sowie informationslogistisch relevante Kontextaspekte identifiziert und durch ein Kontextmodell abgebildet. Für die Formalisierung der unterschiedlichen Einflüsse verschiedener Kontextaspekte auf die Ausgestaltung des Informationsbedarfs wird ein Regelsystem entwickelt, mit dem kontextadaptive Multimodellvorlagen definiert werden können. Durch Auswertung dieser Vorlagen zum Anwendungszeitpunkt lässt sich ein situativer Informationsbedarf antizipieren, auf dessen Basis ein kontextgerechtes Multimodell erzeugt werden kann. Dieser Ansatz ermöglicht die Realisierung einer kontextbewussten Informationslogistik, die den Projektpartnern im Bauwesen genau die Informationsräume bereitstellt, die in einer konkreten Bearbeitungssituation benötigt werden. Für die Bearbeitung regelbasierter Kontextwirkrelationen wird ein Editor vorgestellt, der die Erzeugung kontextadaptiver Multimodellvorlagen unterstützt. Außerdem wird anhand einer Architektur zur Erzeugung kontextgerechter Informationsräume die Vorgehensweise der informationslogistischen Kontextintegration beschrieben, mit der ein kontextbasierter Informationsbedarf antizipiert und ein entsprechendes kontextgerechtes Multimodell erzeugt werden kann. Der Einsatz des vorgestellten Ansatzes wird abschließend anhand eines Beispielszenarios aus der Planungsphase evaluiert, in der im Rahmen verschiedener asynchroner Bauinformationsprozesse Informationsräume gemeinsam bearbeitet werden. / The planning and creating of structures and buildings is based on building information processes, in which linked specialized models of different domains are used as multidisciplinary information spaces. Thereby increased requirements for specialized work processes, and the growing complexity of construction projects lead to an increase in the amount, scope and complexity of the exchanged information spaces. When considering the information requirements of building information processes, a contextdependence is revealed that determines the quantity and quality as well as the cutouts and linking depth of the required information spaces depending on various aspects of the processing context. This thesis addresses contextoriented information supply for collaborative information processes in the construction industry. Based on multimodel information spaces, an approach is presented that formalizes the context dependency of information requirements by contextadaptive multimodel templates and generates corresponding contextoriented information spaces. In a first step different aspects of the process context of building information processes are considered and logistically relevant information are identified and mapped by a context model. For the description of the different influences of various context aspects on the configuration of information needs a regulating system is developed, which can be used to define contextadaptive multi model templates. By evaluating these templates at time of use, situative information requirements can be anticipated and an adequate contextoriented multimodel can be generated. This approach enables the implementation of a contextaware information logistics, which accurately provides the information spaces for the project partners in the construction industry, which are needed in a concrete working situation. For the processing of rulebased context active relations an editor, which supports the generation of contextadaptive multi model templates, is presented. Based on architecture for generating contextappropriate information spaces, the approach of information logistics context integration is described, which allows to anticipate contextbased information needs and to generate a corresponding contextoriented multimodel. The use of the approach is finally evaluated using an example scenario from the planning phase, in which various asynchronous building information processes jointly process an information space.

Les méthodes de synthèse et de validation de lois de pilotage utiliséesdans le milieu industriel aéronautique sont bien souvent longues et coûteuses àmettre en œuvre. Pourtant, des alternatives pour traiter les larges domaine d’évolutionexistent, comme l’inversion dynamique robuste. Ce travail de thèse chercheà en corriger les défauts, notamment grâce à une meilleure prise en compte desincertitudes du système et à une réjection des non-linéarités non compensées. Ceciest rendu possible grâce aux techniques de synthèse H¥ structurée multi-modèles,qui peuvent considérer plusieurs configurations pire-cas déterminées par des outilsd’analyse de robustesse. Une autre contribution est d’ailleurs l’amélioration destechniques permettant d’évaluer la marge de robustesse d’un système LTI, souventtrop conservatives ou nécessitant un temps de calcul prohibitif. Les méthodes proposéessont appliquées au pilotage automatique d’un avion civil et d’un drone àvoilure fixe, dont la modélisation est également traitée avec précision. / Control laws design and validation methods used in the aeronautical industryare generally time-consuming and costly to set up. However, alternativesexist to cope with large operating domains, such as robust dynamic inversion.This thesis work aims at fixing its drawbacks by better considering the systemuncertainties, and by rejecting the uncompensated nonlinearities. Thanks to recentadvances in structured multimodel H¥ design techniques, it is now possible toconsider multiple worst-case configurations, determined using robustness analysistools. Besides, another part of this work is devoted to the improvement of existingtechniques to evaluate the robustness margin of an LTI system, which are oftentoo conservative or computationally costly. All these contributions are applied tothe control of a civil aircraft and a small fixed-wing UAV, whose modeling is alsothoroughly described.